• To authenticate with GitHub, run:

gh auth login

• Follow the instructions to authenticate with GitHub. Select GitHub.com

❯ gh auth login
? Where do you use GitHub?  [Use arrows to move, type to filter]
> GitHub.com
  Other

• You will be asked to open a browser and authenticate with GitHub. Select HTTPS

❯ gh auth login
? Where do you use GitHub? GitHub.com
? What is your preferred protocol for Git operations on this host?  [Use arrows to move, type to filter]
> HTTPS
  SSH

? Authenticate Git with your GitHub credentials? (Y/n) Y

• You will be asked to login

? How would you like to authenticate GitHub CLI?  [Use arrows to move, type to filter]
> Login with a web browser
  Paste an authentication token

• Copy the code and press Enter to go to the browser. Press Continue, paste the code, and click on Authorize

! First copy your one-time code: 1111-AAAA
Press Enter to open github.com in your browser... 

• If successful, you will see:

✓ Authentication complete.
- gh config set -h github.com git_protocol https
✓ Configured git protocol
✓ Logged in as danilofreire

• And you’re done! 🎉

• Now that you have gh installed, you can use Copilot in the CLI
• To install Copilot, run:

gh extension install github/gh-copilot

• And you should be ready to go! 🚀
• GitHub Copilot in the CLI offers two primary commands
  • Explain Command: Use gh copilot explain followed by a command to get an explanation
  • Suggest Command: Use gh copilot suggest followed by a prompt to generate code

• You can also create aliases for these commands. For example:
  • ghce for gh copilot explain
  • ghcs for gh copilot suggest
• If you use zsh, you can just copy the commands below in your terminal:

echo 'eval "$(gh copilot alias -- zsh)"' >> ~/.zshrc && source ~/.zshrc

• Or if you use bash:

echo 'eval "$(gh copilot alias -- bash)"' >> ~/.bashrc && source ~/.bashrc

• Windows PowerShell users can use:

$GH_COPILOT_PROFILE = Join-Path -Path $(Split-Path -Path $PROFILE -Parent) -ChildPath "gh-copilot.ps1"
gh copilot alias -- pwsh | Out-File ( New-Item -Path $GH_COPILOT_PROFILE -Force )
echo ". `"$GH_COPILOT_PROFILE`"" >> $PROFILE

• Let’s see some examples!

• Let’s start with gh copilot explain to get an explanation of a command
• The command below searches for log files and then searches within them for the word error
  • find / -name '*.log' -exec grep 'error' {} +

• Now let’s use gh copilot suggest to generate a command
• ghcs "create three txt files with names test1.txt, test2.txt, and test3.txt", then add the content "Hello, world!" to each file, then list the files, show the content of each file, and delete them"

• Let’s see how Copilot can help with Git commands
• ghcs "create a new branch called 'feature-branch', switch to it, create a new file called 'feature.txt', add some content to it, commit the changes, push the branch to the remote repository, and open a pull request"

• ghcs "how can I use gh to create a new private repository on GitHub danilofreire/testing, clone it to my computer, add a README file, commit the changes, push the changes to the remote repository, and open a pull request?"

• If you have installed Copilot in VS Code, just click on the Copilot icon (a chat bubble) in the bottom left corner
• You can then type a prompt and see the suggestions. As you know how to ask it to generate code (same as in ChatGPT), let’s see other things that Copilot can do for you
• Type /help to see the available commands
• You will also note that there are commands such as @workspace, @vscode, @terminal, and @github that allow you to interact with the workspace, VS Code, the terminal, and GitHub (including your account), respectively
• You can also interact with files with #file
• Let’s have a look at some examples

• Type /explain followed by a code snippet to get an explanation. You can select the snippet directly in the terminal, then just type /explain

• Type /tests followed by a code snippet to run tests
• Let’s see how it tests this function:

class SimpleCalculator:
    def add(self, a, b):
        return a + b

    def subtract(self, a, b):
        return a - b

    def multiply(self, a, b):
        return a * b

    def divide(self, a, b):
        if b == 0:
            raise ValueError("Cannot divide by zero")
        return a / b

    def square_root(self, a):
        if a < 0:
            raise ValueError("Cannot calculate square root of a negative number")
        return a ** 0.5

• Type /fix followed by a code snippet to fix it
• This function is supposed to check if a number is even, but it has a logical error. The division operation (number / 2) should be replaced with the modulo operation (number % 2)
• If you hoover over the Fixed Code block, you will see the options:
  • Apply the fix in the editor
  • Insert the fixed code at the cursor
  • Copy the fixed code to the clipboard
  • Insert into a terminal
  • Insert into a new file

def is_even(number):
    return number / 2 == 0

• Type /new and pass the information about the file you want to create
• /new create a file.txt file with the first three lines of Homer's Odyssey

• You can use the @terminal command to write and run code in the terminal. Click on the terminal icon to insert the code
• @terminal create a file titled test.py and add print("Hello, world!") using the command line

• You can use the @github command to interact with GitHub
• For example, let’s see what are the latest 3 commits of this repository (danilofreire/qtm350)
• You can also use @github to create a new repository, open a pull request, and more

• You can use the @vscode command to interact with VS Code
• For example, let’s see how to open a new file in the editor

• The @workspace command allows you to interact with the workspace, which are the files and folders you have open in VS Code
• For example, let’s ask it to list the files in the workspace

• Another example: let’s ask it to find files that contains bash commands
• Click on the icons and they will open!

• You can use the #file command to search for text in files
• Combine it with the @workspace command to search in all files in the workspace
• Let’s search for Python code in this file

• Now, let’s go back to Roo Code settings and add the API key
• Just copy and paste the key in the OpenRouter API Key field
• We are almost ready to go!
• The last step is to select the models we want to use
• Model choice depends on the task you have at hand, but a general model is a good start
• Note that here we are not running the models locally, but running them on (someone else’s) server
  • So while you gain speed, you lose privacy

• So far, we have seen how to use Roo Code to interact with APIs
• It already saves you a lot of time, as you don’t have to go to a website to get the information you need
• But what if you could automate even more tasks?
• That’s where agents come in!
• Agents are like chatbots that can act autonomously, including running code, sending emails, and interacting with websites
• This is the future of AI, and it is already here!
• For coders, one of the best uses of agents is to let it write and run code for you
• It is the closest thing to “vibes programming” (😂) we have so far

• Let’s ask Roo Code to do the following:
  • Create a new folder called document
  • Create a new Quarto file called api.qmd
  • Write a few paragraphs about the importance of APIs
  • Save the file
  • Render the file and open it in VSCode
  • We could ask it to send it to GitHub, but we will do it manually just for the sake of it
• Prompt:
  • “Create a new folder called document in my current folder. Create a new Quarto file called api.qmd. Write three paragraphs about the importance of APIs. Save the file. Render the file and open it in VSCode.”
• And see the magic happen! 🪄

• It’s super easy to create a Google API key! You can do it in a few steps:
• Go to the Google Cloud Console and sign in with your Google account
• Create a new project or select an existing one (you can name it whatever you want)
• Now, go to https://aistudio.google.com/apikey and click on “Get API Key” and “Create API Key”
• Select the project you created or selected earlier
• Copy the API key and paste it in the .env file in the GOOGLE_API_KEY field
• Check if you are using the Free Plan (no credit card needed)
• And that’s it! You are ready to use Google Gemini in Browser-use! 🤖

https://console.cloud.google.com/

https://aistudio.google.com/apikey

• Here is an example of the .env file
• You just need to add your API key to the GOOGLE_API_KEY field and you are good to go!

OPENAI_ENDPOINT=https://api.openai.com/v1
OPENAI_API_KEY=

ANTHROPIC_API_KEY=

GOOGLE_API_KEY=XXXXXXXX

AZURE_OPENAI_ENDPOINT=
AZURE_OPENAI_API_KEY=

DEEPSEEK_ENDPOINT=https://api.deepseek.com
DEEPSEEK_API_KEY=

• To run the server, just type the command below in the web-ui folder:
  • python webui.py --ip 127.0.0.1 --port 7788
  • If you need to install dotenv, you can do it by running uv pip install python-dotenv
  • Then run .venv/bin/python webui.py --ip 127.0.0.1 --port 7788

Task: go to google.com and find out who won the Oscar for best international film in 2025

Result: The Guardian article says 'I’m Still Here wins Oscar for best international film, becoming first Brazilian film to do so'

• We can run LLMs locally using Ollama and LM Studio
  • Ollama is a command-line tool that allows you to run pre-trained models on your computer
  • LM Studio is a graphic interface that allows you to run any model from Hugging Face
• We can interact with APIs using Roo Code
  • Roo Code is an extension for VSCode that allows you to interact with many APIs
  • You can use it to run code, write text, and analyse images faster
• We can use agents to automate tasks
  • Agents are like chatbots that can act autonomously
• We can browse the internet straight from our code editor
  • Browser-use is a Python library that allows you to interact with websites, extract information, and perform tasks
  • It comes with a web interface that allows you to interact with websites visually